At Insights Association’s Ignite Data Quality Event, the future of data quality took center stage, and the message was clear: technology is evolving fast, but people are still at the heart of meaningful insights. From human-driven interpretation to AI oversight, here’s what’s shaping the next generation of consumer research.
1. Data Quality Starts and Ends with People
2. Transparency in Sampling is Non-Negotiable
As the sampling ecosystem shifts from proprietary panels to affiliate networks and exchanges, transparency is more important than ever. Hidden sourcing practices and undisclosed sub-suppliers undermine trust and put data integrity at risk. Leaders in the industry, like P&G, are now mandating certifications such as ISO 20252 by July 2025 to raise the bar. Moving forward, full disclosure of all sub-sources must be a contractual standard to protect quality at every step.
3. AI is a Tool, Not a Replacement
AI’s role in data quality is powerful but it’s not a substitute for human oversight. While AI improves efficiency in areas like pre-survey screening, it can either over-correct (excluding good respondents) or under-correct (letting fraudulent data through). The solution? A "human-in-the-loop" model that combines the speed of AI with human validation, ensuring that technology enhances rather than replaces critical decision-making.
4. Respect the Respondent Experience
Flawed data often starts with a disengaged participant. To tackle this, the industry is adopting these key principles: Respect respondent time, ensure honesty, reduce fatigue, and offer clean survey endings. Pilot testing for flow, clarity, and engagement is now a non-negotiable best practice. After all, a better experience for participants leads to better outcomes for researchers.
5. Innovation in Recruitment and Quality Testing
New approaches are revitalizing recruitment and quality control. "Qualtchas" - interactive, logic-driven, and even video-based validation tools - are replacing static red herrings. In health tech research, influencer-led recruiting combined with direct outreach achieved an impressive 93% completion rate over six weeks, even in logistically challenging environments. Additionally, culturally intelligent recruiting, especially among Hispanic audiences, now emphasizes nuanced identity markers over binary labels. Asking about values, lifestyle, and language provides richer, more authentic data.
The Bottom Line
The future of data quality isn’t about choosing between people and technology - it’s about blending the strengths of both. Emotional intelligence, ethical sampling practices, respectful participant experiences, and thoughtful use of AI are shaping a more resilient, reliable, and human-centered research landscape. As we move forward, quality will come from those who can master both empathy and innovation.
THE AUTHOR
Anne Martin is the Vice President of Field Operations at Behaviorally, where she specializes in market research operations and procurement. She focuses on optimizing workflows and ensuring high-quality deliverables for clients. Anne is dedicated to maintaining quality control and upholding the integrity of research in an ever-evolving data landscape.
Outside of work, Anne enjoys traveling and discovering great places to recharge, as well as spending time with her dogs.
